TAToo: Vision-based Joint Tracking of Anatomy and Tool for Skull-base Surgery
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Abstract (arXiv)
Purpose: Tracking the 3D motion of the surgical tool and the patient anatomy is a fundamental requirement for computer-assisted skull-base surgery. The estimated motion can be used both for intra-operative guidance and for downstream skill analysis. Recovering such motion solely from surgical videos is desirable, as it is compliant with current clinical workflows and instrumentation. Methods: We present Tracker of Anatomy and Tool (TAToo). TAToo jointly tracks the rigid 3D motion of patient skull and surgical drill from stereo microscopic videos. TAToo estimates motion via an iterative optimization process in an end-to-end differentiable form. For robust tracking performance, TAToo adopts a probabilistic formulation and enforces geometric constraints on the object level. Results: We validate TAToo on both simulation data, where ground truth motion is available, as well as on anthropomorphic phantom data, where optical tracking provides a strong baseline. We report sub-millimeter and millimeter inter-frame tracking accuracy for skull and drill, respectively, with rotation errors below 1deg. We further illustrate how TAToo may be used in a surgical navigation setting. Conclusion: We present TAToo, which simultaneously tracks the surgical tool and the patient anatomy in skull-base surgery. TAToo directly predicts the motion from surgical videos, without the need of any markers. Our results show that the performance of TAToo compares favorably to competing approaches. Future work will include fine-tuning of our depth network to reach a 1 mm clinical accuracy goal desired for surgical applications in the skull base.
Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). Builds on 16 of its 40 references that are in the map. First posted on arXiv 29 Dec 2022.
Builds on
16 of 40 references.
References · 16
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- 2022Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgerycited by 123
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- 2020Neural Non-Rigid Trackingcited by 49
- 2021E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perceptioncited by 46
4 more
- 2021Tangent Space Backpropagation for 3D Transformation Groupscited by 40
- 2022SAGE: SLAM with Appearance and Geometry Prior for Endoscopycited by 28
- 2021Temporally Consistent Online Depth Estimation in Dynamic Scenescited by 26
- 2021Virtual Reality for Synergistic Surgical Training and Data Generationcited by 6
Built on by
Citing papers per year: 2023: 1; 2024: 0; 2025: 1; 2026: 1.
3 papers.
- 2023Unidirectional brain-computer interface: Artificial neural network encoding natural images to fMRI response in the visual cortexcited by 2
- 2025SurgiSR4K: A High-Resolution Endoscopic Video Dataset for Robotic-Assisted Minimally Invasive Procedurescited by 2
- 2026Speak, Segment, Track, Navigate: An Interactive System for Video-Guided Skull-Base Surgerycited by 1
- 2026Speak, Segment, Track, Navigate: An Interactive System for Video-Guided Skull-Base Surgery17 Mar 2026
- 2025SurgiSR4K: A High-Resolution Endoscopic Video Dataset for Robotic-Assisted Minimally Invasive Procedures30 Jun 2025
- 2023Unidirectional brain-computer interface: Artificial neural network encoding natural images to fMRI response in the visual cortex26 Sep 2023